Random number generation is an important element of many cryptographic services. Random numbers are used to initialize cryptographic sequences, generate keys, create authentication challenges, and more. However, if the random number comes from a source that is predictable or lacks sufficient entropy, this could become a weakness that can be exploited to break the encryption and expose secrets. For computational efficiency, many modern systems feature a Pseudorandom Number Generator (PRNG), sometimes also called a Deterministic Random Bit Generator (DRBG). A pseudorandom number generator generates a deterministic sequence of numbers using a mathematical algorithm, but is dependent on an initial random seed. A true random number generator (TRNG) uses physical sources of randomness such as noise or quantum phenomena to generate bits that are truly random and independent, but is typically much slower than a PRNG. A common practice is to use a TRNG to provide a high-entropy random seed to initialize the PRNG, which is then used to generate the random numbers for the cryptographic application.